Field of the Invention
The present invention relates to a technique for classifying an object in an image.
Description of the Related Art
There is proposed a technique for classifying a specific object such as a human body or face in an image. Particularly, in recent years, a high-speed low-cost object classification method for an embedded system such as a mobile terminal or a device installed in a car has received attention.
In P. Viola, M. Jones, “Rapid Object Detection using a Boosted Cascade of Simple Features”, Proc. IEEE Conf. on Computer Vision and Pattern Recognition, Vol. 1, pp. 511-518, December 2001, an algorithm for increasing the speed of object detection is proposed. According to this algorithm, weak classifiers in a series generated by boosting learning are sequentially processed. Then, based on the classification result of each weak classifier, whether to process the next weak classifiers is determined. If it is determined not to process the next weak classifiers, the processing of the remaining weak classifiers is omitted.
Japanese Patent Laid-Open No. 2012-247940 proposes a technique to efficiently perform classification processing. As a method of solution, the processing time is reduced by efficiently combining spatial parallelism and pipeline parallelism.
In Junguk Cho, et al., “Hardware acceleration of multi-view face detection,” IEEE 7th Symposium on Application Specific Processors, pp. 66-69, July 2009, a hardware implementation method for increasing the speed of face detection is proposed. In this method, weak classifiers for classifying faces of a plurality of categories (the orientation and the like) are processed by spatial parallelism to reduce the processing time.
Classification processing by a plurality of cascade-connected weak classifiers (Japanese Patent Laid-Open No. 2012-247940, P. Viola, M. Jones, “Rapid Object Detection using a Boosted Cascade of Simple Features”, Proc. IEEE Conf. on Computer Vision and Pattern Recognition, Vol. 1, pp. 511-518, December 2001, and Junguk Cho, et al., “Hardware acceleration of multi-view face detection,” IEEE 7th Symposium on Application Specific Processors, pp. 66-69, July. 2009) is a technique often used as a high-speed and low-cost method for object classification. To improve the classification accuracy of the classification target for all kinds of orientation variations of the classification target object, there is a method that categorizes the variations and performs classification by using a plurality of weak classifiers set in a cascade arrangement for each category. The total number of weak classifiers increases together with the increase in the categories of classification targets.
In order to increase the speed of the weak classifiers corresponding to the plurality of categories, a processing device is provided for each category and weak classifiers of a plurality of categories are simultaneously processed in Junguk Cho, et al., “Hardware acceleration of multi-view face detection,” IEEE 7th Symposium on Application Specific Processors, pp. 66-69, July. 2009. However, since the processing end times of the weak classifiers of the respective categories vary, the processing device of each category that has completed the processing is not used and the idle time is long. Therefore, in order to perform real-time object classification processing that corresponds to a plurality of categories in an embedded system, it is necessary to use and rapidly process a limited number of processing devices.